Adaptive shape coding for perceptual decision in the human brain.
Abstract.
In our search for neural codes, we have uncovered neural representations that reflect the structure of stimuli of variable complexity from simple features to objet categories. However, accumulating evidence suggests an adaptive neural code that is dynamically shaped by experience to support flexible and efficient perceptual decisions. Here, we present work showing that experience plays a critical role in moulding mid-level visual representations for perceptual decisions. Combining behavioral and brain imaging measurements we demonstrate that learning optimizes feature binding for object recognition in cluttered scenes, and tunes the neural representations of informative image parts to support efficient categorical judgments. Our findings propose that similar learning mechanisms may mediate long-term optimization through development, tune the visual system to fundamental principles of feature binding, and optimize feature templates for perceptual decisions.